Triple
T23044065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-77 |
E573824
|
entity |
| Predicate | crewMember |
P2094
|
FINISHED |
| Object | Mario Runco Jr. |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Mario Runco Jr. | Statement: [STS-77, crewMember, Mario Runco Jr.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mario Runco Jr. Context triple: [STS-77, crewMember, Mario Runco Jr.]
-
A.
Mario Runco Jr.
chosen
Mario Runco Jr. is a former NASA astronaut and U.S. Navy officer who flew on multiple Space Shuttle missions in the 1990s.
-
B.
Baby Mario
Baby Mario is the infant version of Nintendo’s iconic hero Mario, appearing as a playable character in various Mario spin-off and Yoshi games.
-
C.
Mario the Magnificent
Mario the Magnificent is the dragon mascot of Drexel University, symbolizing the school's spirit and identity at athletic events and campus activities.
-
D.
Bee Mario
Bee Mario is a special transformation of Mario in the Super Mario series that lets him fly short distances, cling to honeycomb walls, and walk on flowers while wearing a fuzzy bee suit.
-
E.
Hotel Mario
Hotel Mario is a 1994 Philips CD-i puzzle-platform video game based on the Mario franchise, infamous for its poor quality and awkward full-motion video cutscenes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e245b9c11481909d06c872214d21af |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18517083c8190a0850da5440e0a73 |
completed | April 29, 2026, 4:12 a.m. |
Created at: April 17, 2026, 3:54 p.m.